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Exploring Causes of Representational Similarity in Machine Learning Models

Exploring Causes of Representational Similarity in Machine Learning Models

20 May 2025
Zeyu Michael Li
Hung Anh Vu
Damilola Awofisayo
Emily Wenger
    CML
ArXivPDFHTML

Papers citing "Exploring Causes of Representational Similarity in Machine Learning Models"

36 / 36 papers shown
Title
We're Different, We're the Same: Creative Homogeneity Across LLMs
We're Different, We're the Same: Creative Homogeneity Across LLMs
Emily Wenger
Yoed Kenett
118
9
0
31 Jan 2025
Objective drives the consistency of representational similarity across datasets
Objective drives the consistency of representational similarity across datasets
Laure Ciernik
Lorenz Linhardt
Marco Morik
Jonas Dippel
Simon Kornblith
Lukas Muttenthaler
58
5
0
08 Nov 2024
Jamba-1.5: Hybrid Transformer-Mamba Models at Scale
Jamba-1.5: Hybrid Transformer-Mamba Models at Scale
Jamba Team
Barak Lenz
Alan Arazi
Amir Bergman
Avshalom Manevich
...
Yehoshua Cohen
Yonatan Belinkov
Y. Globerson
Yuval Peleg Levy
Y. Shoham
84
32
0
22 Aug 2024
The Platonic Representation Hypothesis
The Platonic Representation Hypothesis
Minyoung Huh
Brian Cheung
Tongzhou Wang
Phillip Isola
110
134
0
13 May 2024
AI and the Problem of Knowledge Collapse
AI and the Problem of Knowledge Collapse
Andrew J. Peterson
78
22
0
04 Apr 2024
Neural Redshift: Random Networks are not Random Functions
Neural Redshift: Random Networks are not Random Functions
Damien Teney
A. Nicolicioiu
Valentin Hartmann
Ehsan Abbasnejad
139
24
0
04 Mar 2024
Universal Neurons in GPT2 Language Models
Universal Neurons in GPT2 Language Models
Wes Gurnee
Theo Horsley
Zifan Carl Guo
Tara Rezaei Kheirkhah
Qinyi Sun
Will Hathaway
Neel Nanda
Dimitris Bertsimas
MILM
131
46
0
22 Jan 2024
Towards Measuring Representational Similarity of Large Language Models
Towards Measuring Representational Similarity of Large Language Models
Max Klabunde
Mehdi Ben Amor
Michael Granitzer
Florian Lemmerich
59
4
0
05 Dec 2023
Fantastic Gains and Where to Find Them: On the Existence and Prospect of
  General Knowledge Transfer between Any Pretrained Model
Fantastic Gains and Where to Find Them: On the Existence and Prospect of General Knowledge Transfer between Any Pretrained Model
Karsten Roth
Lukas Thede
Almut Sophia Koepke
Oriol Vinyals
Olivier J. Hénaff
Zeynep Akata
AAML
68
12
0
26 Oct 2023
Getting aligned on representational alignment
Getting aligned on representational alignment
Ilia Sucholutsky
Lukas Muttenthaler
Adrian Weller
Andi Peng
Andreea Bobu
...
Thomas Unterthiner
Andrew Kyle Lampinen
Klaus-Robert Muller
M. Toneva
Thomas Griffiths
115
88
0
18 Oct 2023
A Comprehensive Overview of Large Language Models
A Comprehensive Overview of Large Language Models
Humza Naveed
Asad Ullah Khan
Shi Qiu
Muhammad Saqib
Saeed Anwar
Muhammad Usman
Naveed Akhtar
Nick Barnes
Ajmal Mian
OffRL
92
595
0
12 Jul 2023
Large Language Models
Large Language Models
Michael R Douglas
LLMAG
LM&MA
138
628
0
11 Jul 2023
Rosetta Neurons: Mining the Common Units in a Model Zoo
Rosetta Neurons: Mining the Common Units in a Model Zoo
Amil Dravid
Yossi Gandelsman
Alexei A. Efros
Assaf Shocher
44
30
0
15 Jun 2023
Similarity of Neural Network Models: A Survey of Functional and Representational Measures
Similarity of Neural Network Models: A Survey of Functional and Representational Measures
Max Klabunde
Tobias Schumacher
M. Strohmaier
Florian Lemmerich
133
73
0
10 May 2023
LLaMA: Open and Efficient Foundation Language Models
LLaMA: Open and Efficient Foundation Language Models
Hugo Touvron
Thibaut Lavril
Gautier Izacard
Xavier Martinet
Marie-Anne Lachaux
...
Faisal Azhar
Aurelien Rodriguez
Armand Joulin
Edouard Grave
Guillaume Lample
ALM
PILM
1.5K
13,247
0
27 Feb 2023
Relative representations enable zero-shot latent space communication
Relative representations enable zero-shot latent space communication
Luca Moschella
Valentino Maiorca
Marco Fumero
Antonio Norelli
Francesco Locatello
Emanuele Rodolà
72
106
0
30 Sep 2022
Toward Transparent AI: A Survey on Interpreting the Inner Structures of
  Deep Neural Networks
Toward Transparent AI: A Survey on Interpreting the Inner Structures of Deep Neural Networks
Tilman Raukur
A. Ho
Stephen Casper
Dylan Hadfield-Menell
AAML
AI4CE
93
132
0
27 Jul 2022
PaLM: Scaling Language Modeling with Pathways
PaLM: Scaling Language Modeling with Pathways
Aakanksha Chowdhery
Sharan Narang
Jacob Devlin
Maarten Bosma
Gaurav Mishra
...
Kathy Meier-Hellstern
Douglas Eck
J. Dean
Slav Petrov
Noah Fiedel
PILM
LRM
486
6,240
0
05 Apr 2022
Divergent representations of ethological visual inputs emerge from
  supervised, unsupervised, and reinforcement learning
Divergent representations of ethological visual inputs emerge from supervised, unsupervised, and reinforcement learning
Grace W. Lindsay
J. Merel
T. Mrsic-Flogel
M. Sahani
SSL
DRL
69
6
0
03 Dec 2021
Revisiting Model Stitching to Compare Neural Representations
Revisiting Model Stitching to Compare Neural Representations
Yamini Bansal
Preetum Nakkiran
Boaz Barak
FedML
90
117
0
14 Jun 2021
Towards Understanding Knowledge Distillation
Towards Understanding Knowledge Distillation
Mary Phuong
Christoph H. Lampert
65
319
0
27 May 2021
Do Wide and Deep Networks Learn the Same Things? Uncovering How Neural
  Network Representations Vary with Width and Depth
Do Wide and Deep Networks Learn the Same Things? Uncovering How Neural Network Representations Vary with Width and Depth
Thao Nguyen
M. Raghu
Simon Kornblith
OOD
52
282
0
29 Oct 2020
On Linear Identifiability of Learned Representations
On Linear Identifiability of Learned Representations
Geoffrey Roeder
Luke Metz
Diederik P. Kingma
CML
60
81
0
01 Jul 2020
Beyond accuracy: quantifying trial-by-trial behaviour of CNNs and humans
  by measuring error consistency
Beyond accuracy: quantifying trial-by-trial behaviour of CNNs and humans by measuring error consistency
Robert Geirhos
Kristof Meding
Felix Wichmann
63
123
0
30 Jun 2020
What shapes feature representations? Exploring datasets, architectures,
  and training
What shapes feature representations? Exploring datasets, architectures, and training
Katherine L. Hermann
Andrew Kyle Lampinen
OOD
82
157
0
22 Jun 2020
Language Models are Few-Shot Learners
Language Models are Few-Shot Learners
Tom B. Brown
Benjamin Mann
Nick Ryder
Melanie Subbiah
Jared Kaplan
...
Christopher Berner
Sam McCandlish
Alec Radford
Ilya Sutskever
Dario Amodei
BDL
795
42,055
0
28 May 2020
Scaling Laws for Neural Language Models
Scaling Laws for Neural Language Models
Jared Kaplan
Sam McCandlish
T. Henighan
Tom B. Brown
B. Chess
R. Child
Scott Gray
Alec Radford
Jeff Wu
Dario Amodei
605
4,822
0
23 Jan 2020
PyTorch: An Imperative Style, High-Performance Deep Learning Library
PyTorch: An Imperative Style, High-Performance Deep Learning Library
Adam Paszke
Sam Gross
Francisco Massa
Adam Lerer
James Bradbury
...
Sasank Chilamkurthy
Benoit Steiner
Lu Fang
Junjie Bai
Soumith Chintala
ODL
499
42,449
0
03 Dec 2019
On the Efficacy of Knowledge Distillation
On the Efficacy of Knowledge Distillation
Ligang He
Rui Mao
94
609
0
03 Oct 2019
An Introduction to Variational Autoencoders
An Introduction to Variational Autoencoders
Diederik P. Kingma
Max Welling
BDL
SSL
DRL
82
2,354
0
06 Jun 2019
Let's Agree to Agree: Neural Networks Share Classification Order on Real
  Datasets
Let's Agree to Agree: Neural Networks Share Classification Order on Real Datasets
Guy Hacohen
Leshem Choshen
D. Weinshall
AI4TS
OOD
62
57
0
26 May 2019
Similarity of Neural Network Representations Revisited
Similarity of Neural Network Representations Revisited
Simon Kornblith
Mohammad Norouzi
Honglak Lee
Geoffrey E. Hinton
141
1,418
0
01 May 2019
Insights on representational similarity in neural networks with
  canonical correlation
Insights on representational similarity in neural networks with canonical correlation
Ari S. Morcos
M. Raghu
Samy Bengio
DRL
63
446
0
14 Jun 2018
Pointer Sentinel Mixture Models
Pointer Sentinel Mixture Models
Stephen Merity
Caiming Xiong
James Bradbury
R. Socher
RALM
319
2,876
0
26 Sep 2016
Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
2.2K
194,020
0
10 Dec 2015
Convergent Learning: Do different neural networks learn the same
  representations?
Convergent Learning: Do different neural networks learn the same representations?
Yixuan Li
J. Yosinski
Jeff Clune
Hod Lipson
John E. Hopcroft
SSL
86
370
0
24 Nov 2015
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